Stochastic effects in lifespan determination

Pharyngula has picked up a Nature Genetics paper about the influence of stochastic, non-heritable effects in determining lifespan in the worm C. elegans. I’d encourage you to read PZ’s lengthy analysis yourself, but here’s an excerpt of the summary portion of his posting:

…[I]n humans only about 25% of the variation in life span can be ascribed to genetic factors to any degree, and even in lab animals where variables can be greatly reduced, only 10-40% of the life span variation has a genetic component. … Life is like a long dice game, and while starting with a good endowment might let you keep playing for a longer time, eventually everyone craps out, and a run of bad luck can wipe out even the richest starting position rapidly.

In between these extremes of genetic predetermination and pure luck, though, a recent paper in Nature Genetics finds another possibility: factors in the organism that are not heritable, yet from an early age can be reasonably good predictors of mortality.

Here’s the experiment. Start with an isogenic line of Caenorhabditis elegans … When raising a colony of isogenic animals, of course, they don’t all abruptly kick the bucket on the same day at the end of their maximum lifespan (under two months for these worms), but instead a few die every day until they are all gone. The question is, is there anything that will allow one to predict whether a newly hatched worm will die in one week, or in 8 weeks?

The specific variable studied is the extent of expression of an hsp-16.2-GFP transgene. The authors find that among an isogenic population, worms with the highest level of transgene expression in early life live the longest. (That animals with higher chaperone expression live longer is not particularly surprising in itself; the key result of the paper is that genetically identical animals express this particular chaperone to varying degrees, and the particular level of early-life chaperone expression in a particular animal has a significant impact on how long that individual will ultimately live.)

Hence early-life variation can control late-life outcomes, consistent with the observations of McCarroll et al., who showed in 2004 that much of the conserved transcriptional program of aging is implemented in early adulthood.

The study of variation in gene expression, already underway in relationship to aging (see our earlier post, Genomic instability and transcriptional noise), is almost exclusively performed in single cells. It’s exciting to see it happening in an intact metazoan, and furthermore to see the impact of the observed variation on a physiological endpoint of such significance (i.e., lifespan).